Phylogenies from amino acid sequences aligned with gaps: The problem of gap weighting

Summary The common but generally overlooked problem of how best to construct phylogenies from orthologous amino acid sequences, when their alignment requires the placement therein of gaps denoting insertions/deletions in the evolutionary history of their genes since their common ancestor, has been studied. Three diverse methods were examined: 1. each missing residue in a gap is weighted as equivalent to the average number of minimum nucleotide replacements in known conjugate amino acid pairs of those same two sequences, which weight necessarily differs for each pair of sequences; 2. each missing residue in a gap is weighted as equivalent to a fixed number of nucleotide replacements; and 3. each gap, regardless of length, is weighted as equivalent to a fixed number of nucleotide replacements. For the flavodoxins, each method yielded a different best tree and suggests that the choice of method may be crucial. For the plant ferredoxins, all methods give results inconsistent with botanical classification and suggests the sequences may not all be orthologous. For the bacterial ferredoxins, the method was less germane than the actual weight used, five different best trees being obtained depending upon the weight. The best tree for all ferredoxins (prokaryotic plus eukaryotic) combined proved to be greatly dependent upon the gap locations with several reasonable alignments yielding different best trees. They also suggest that functional equivalence may well prove to be a poor guide to which residues have a common ancestral codon. The rubredoxin sequences show that a partial internal gene duplication occurred in thePseudomonas line, probably very soon after its divergence from the other genera. Together, the results clearly indicate that the phylogenetic answer one gets may greatly depend upon how one treats the gaps but they fail to indicate what treatment may be best. This results partly from the fact that the phylogenies of the taxa represented are not known with sufficient confidence to be sure when the procedures are performing best.     

Identification of a key amino acid residue of Streptomyces phospholipase D for thermostability by in vivo DNA shuffling

To isolate thermostability-related amino acid residues of Streptomyces phospholipase D (PLD), we constructed a chimeral genes library between two highly homologous plds, which exhibited different thermostabilities, by an in vivo DNA shuffling method using Escherichia coli that has a mutation of a single-stranded DNA-binding protein gene. To confirm the location of the recombination site, we carried out the restriction mapping of 68 chimeral pld genes. The recombination sites were widely dispersed over the entire pld sequence. Moreover, we examined six chimeral PLDs by comparing their thermostabilities with those of parental PLDs. To identify a thermostability-related amino acid residue, we investigated the thermostability of chimera C that was the most thermolabile among the six chimeras. We identified the thermostability-related factor Gly-188, which is located in the alpha-7 helix of PLD from Streptomyces septatus TH-2 (TH-2PLD). TH-2PLD mutants, in which Gly-188 was substituted with Phe, Val or Trp, exhibited higher thermostabilities than that of the parental PLD. Gly-188 substituted with the Phe mutant, which was the most stable among the mutants, showed an enzyme activity almost the same as that of TH-2PLD as determine by kinetic analysis.     

Inhibition of enkephalin-degrading enzymes from rat brain and of thermolysin by amino acid hydroxamates

Benzyloxycarbonyl derivatives (Z) of amino acid hydroxamates have been found to inhibit the bacterial metalloendopeptidase thermolysin and enkephalin-degrading enzymes from rat brain. The hydroxamate derivatives of glycine, leucine, phenylalanine and D-phenylalanine inhibit thermolysin with K_I values in the range of 3–23 μM. They also inhibit the enkephalin-degrading endopeptidase (enkephalinase) and aminopeptidase with different efficiencies, depending on the structure of the amino acid employed. Thus, Z-Gly-NHOH inhibits the enkephalinase and aminopeptidase with IC₅₀ values of 1 μM and 300 μM, respectively, whereas Z-D-Phe-NHOH inhibits the corresponding enzymes with IC₅₀ values of 0.2 μM and 1.5 μM.     

Prediction of RNA binding sites in proteins from amino acid sequence

RNA-protein interactions are vitally important in a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed a computational tool for predicting which amino acids of an RNA binding protein participate in RNA-protein interactions, using only the protein sequence as input. RNABindR was developed using machine learning on a validated nonredundant data set of interfaces from known RNA-protein complexes in the Protein Data Bank. It generates a classifier that captures primary sequence signals sufficient for predicting which amino acids in a given protein are located in the RNA-protein interface. In leave-one-out cross-validation experiments, RNABindR identifies interface residues with >85% overall accuracy. It can be calibrated by the user to obtain either high specificity or high sensitivity for interface residues. RNABindR, implementing a Naive Bayes classifier, performs as well as a more complex neural network classifier (to our knowledge, the only previously published sequence-based method for RNA binding site prediction) and offers the advantages of speed, simplicity and interpretability of results. RNABindR predictions on the human telomerase protein hTERT are in good agreement with experimental data. The availability of computational tools for predicting which residues in an RNA binding protein are likely to contact RNA should facilitate design of experiments to directly test RNA binding function and contribute to our understanding of the diversity, mechanisms, and regulation of RNA-protein complexes in biological systems. (RNABindR is available as a Web tool from http://bindr.gdcb.iastate.edu.).     

New enzymes from environmental cassette arrays: functional attributes of a phosphotransferase and an RNA-methyltransferase

By targeting gene cassettes by polymerase chain reaction (PCR) directly from environmentally derived DNA, we are able to amplify entire open reading frames (ORFs) independently of prior sequence knowledge. Approximately 10% of the mobile genes recovered by these means can be attributed to known protein families. Here we describe the characterization of two ORFs which show moderate homology to known proteins: (1) an aminoglycoside phosphotransferase displaying 25% sequence identity with APH(7") from Streptomyces hygroscopicus, and (2) an RNA methyltransferase sharing 25%-28% identity with a group of recently defined bacterial RNA methyltransferases distinct from the SpoU enzyme family. Our novel genes were expressed as recombinant products and assayed for appropriate enzyme activity. The aminoglycoside phosphotransferase displayed ATPase activity, consistent with the presence of characteristic Mg(2+)-binding residues. Unlike related APH(4) or APH(7") enzymes, however, this activity was not enhanced by hygromycin B or kanamycin, suggesting the normal substrate to be a different aminoglycoside. The RNA methyltransferase contains sequence motifs of the RNA methyltransferase superfamily, and our recombinant version showed methyltransferase activity with RNA. Our data confirm that gene cassettes present in the environment encode folded enzymes with novel sequence variation and demonstrable catalytic activity. Our PCR approach (cassette PCR) may be used to identify a diverse range of ORFs from any environmental sample, as well as to directly access the gene pool found in mobile gene cassettes commonly associated with integrons. This gene pool can be accessed from both cultured and uncultured microbial samples as a source of new enzymes and proteins.     

Mutation of a negatively charged amino acid in thioredoxin modifies its reactivity with chloroplastic enzymes.

A new over-expression system has been set up for Escherichia coli thioredoxin, yielding 55 mg purified protein/10 g fresh cells. This system has been used to produce thioredoxin modified by site-directed mutagenesis. Taking advantage of the structural and enzymatic similarity between E. coli and spinach m-type thioredoxin, Asp61 of E. coli thioredoxin has been changed into Asn in order to investigate the impact of the suppression of a charged residue on the interaction of thioredoxin with target enzymes. The modification did not significantly alter the structure of the protein. Neither the rate of reduction of insulin and 5,5'-dithio-bis(2-nitrobenzoic acid) by the reduced thioredoxin, nor the reduction by NADPH-dependent thioredoxin reductase, have been modified. The major effect of the mutation was observed for chloroplast enzyme activation with thioredoxin reduced by dithiothreitol and with thioredoxin reduced by ferredoxin-dependent thioredoxin reductase in a light-activation reconstituted chloroplast system. The substitution of the negatively charged Asp61 by the neutral Asn led to an increase in the efficiency of spinach fructose-1,6-bisphosphatase activation by the dithiothreitol-reduced thioredoxin, and to an increase in both spinach fructose-1,6-bisphosphatase and corn NADP-dependent malate dehydrogenase activities in the light-activation system. This suggests that the suppression of the negative charge improves the reactivity of thioredoxin with chloroplast enzymes such as fructose-1,6-bisphosphatase and ferredoxin-dependent thioredoxin reductase.     

MtArt: a new model of amino acid replacement for Arthropoda

A statistical approach was applied to select those models that best fit each individual mitochondrial (mt) protein at different taxonomic levels of metazoans. The existing mitochondrial replacement matrices, MtREV and MtMam, were found to be the best-fit models for the mt-proteins of vertebrates, with the exception of Nd6, at different taxonomic levels. Remarkably, existing mitochondrial matrices generally failed to best-fit invertebrate mt-proteins. In an attempt to better model the evolution of invertebrate mt-proteins, a new replacement matrix, named MtArt, was constructed based on arthropod mt-proteomes. The new model was found to best fit almost all analyzed invertebrate mt-protein data sets. The observed pattern of model fit across the different data sets indicates that no single replacement matrix is able to describe the general evolutionary properties of mt-proteins but rather that taxonomical biases and/or the existence of different mt-genetic codes have great influence on which model is selected.     

Responses of amino acid metabolizing enzymes from plants differing in salt tolerance to NaCl

Summary This paper reports the effects of NaCl on the in vivo activity of glutamate dehydrogenase (GDH) and glutamic-oxaloacetic transaminase (GOT) and on the in vitro activity of GDH, both enzymes having been isolated from plants differing in salt tolerance. The plants investigated were Vicia faba (salt-sensitive), Atriplex nitens and Atriplex calotheca (more or less salt-tolerant), and Atriplex halimus (halophyte) grown at various NaCl concentrations. GDH and GOT isolated from various salt-tolerant plants grown at low NaCl concentrations were inhibited in a similar way. At high NaCl concentrations, the enzyme activities remain at constant values only in the Atriplex species. GOT was more impaired by NaCl than GDH. In the case of GOT, the double reciprocal plot indicated the type of a noncompetitive inhibition. The in vitro effect of NaCl on the activity of GDH from the differentially salt-tolerant plants was of a different kind, i.e. GDH isolated from V. faba was clearly inhibited by NaCl, whereas NaCl stimulated the activity of GDH from all Atriplex species investigated. Kinetic analysis showed that substrate inhibition of GDH from A. nitens and A. calotheca grown at non-saline conditions could be removed by NaCl. Inhibition by high NaCl concentrations at low substrate concentrations was removable by increasing substrate concentrations. Moreover, the inhibition at low substrate concentrations was shown to be competitive. GDH lost this regulatory property when the plants were pretreated with 500 mM NaCl. GDH from A. halimus also possessed this control, but in contrast to A. nitens and A. calotheca, activity and control of GDH isolated from A. halimus were stimulated by pretreating the plants with 500 mM NaCl. The results showed that DDH isolated from the salt-tolerant Atriplex species was adapted to high NaCl concentrations of the tissue. Possible mechanisms of the interactions between GDH from salt-tolerant Atriplex species and NaCl are discussed.     

Prospects for robust biocatalysis: engineering of novel specificity in a halophilic amino acid dehydrogenase

Heat- and solvent-tolerant enzymes from halophiles, potentially important industrially, offer a robust framework for protein engineering, but few solved halophilic structures exist to guide this. Homology modelling has guided mutations in glutamate dehydrogenase (GDH) from Halobacterium salinarum to emulate conversion of a mesophilic GDH to a methionine dehydrogenase. Replacement of K89, A163 and S367 by leucine, glycine and alanine converted halophilic GDH into a dehydrogenase accepting l-methionine, l-norleucine and l-norvaline as substrates. Over-expression in the halophilic expression host Haloferax volcanii and three-step purification gave ~98 % pure protein exhibiting maximum activity at pH 10. This enzyme also showed enhanced thermostability and organic solvent tolerance even at 70 °C, offering a biocatalyst resistant to harsh industrial environments. To our knowledge, this is the first reported amino acid specificity change engineered in a halophilic enzyme, encouraging use of mesophilic models to guide engineering of novel halophilic biocatalysts for industrial application. Calibrated gel filtration experiments show that both the mutant and the wild-type enzyme are stable hexamers.     

Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition

A new representation of protein sequence is devoted in this paper, in which each protein can be represented by a 20-dimensional (20D) vector of unit length. Inspired by the principle of superposition of state in quantum mechanics, the squares of the 20 components of the vector correspond to the amino acid composition. Using the new representation of the primary sequence and Bayes Discriminant Algorithm, the subcellular location of prokaryotic proteins was predicted. The overall predictive accuracy in the jackknife test can be 3% higher than the result of using amino acid composition directly for the database of sequence identity is less than 90%, but 5% higher when sequence identity is less than 80%. The higher predictive accuracy indicates that the current measure of extracting the information from the primary sequence is efficient. Since the subcellular location restricting a protein's possible function, the present method should also be a useful measure for the systematic analysis of genome data. The program used in this paper is available on request.     

Metabolic engineering from a cybernetic perspective: aspartate family of amino acids

Using the modular cybernetic framework developed by Varner and Ramkrishna (Varner and Ramkrishna; 1998a, b) a cybernetic model is formulated that describes the time evolution of the aspartate family of amino acids in Corynebacterium lactofermentum ATCC 21799. The network model formulation is employed in the role of a diagnostic tool for the overproduction of threonine. More precisely, having determined a parameter set that describes the time evolution of a base strain (lysine producer), the model predicted response to genetic perturbations, designed to enhance the level of threonine, are simulated using an appropriately modified cybernetic model and compared with the experimental results of Stephanopoulos and Sinskey (Colón et al., 1995a, Appl. Environ. Microbiol. 61, 74-78) for identical genetic perturbations. It is found that the model predicted response to enzymatic over-expression in the aspartate pathway agrees, for the most part, with experimental observations within the experimental error bounds. This result lends credence to the hypothesis that cybernetic models can be employed to predict the local response of a metabolic network to genetic perturbation, thereby, affording cognizance of the potential pitfalls of a particular genetic alteration strategy a priori.